Why people leave your company

Linnea Bywall

  -  

May 15, 2019

The Cost of Churn

In a world where competition for talent is fierce, and competent employees are the number one asset of any company, no organization can afford not to think about churn. Retaining top talent is essential for organizational knowledge, high morale, satisfied customers, and sales growth.

Also known by its more formal name turnover rate, churn is the number of employees that have left, divided by the total number of employees, usually measured on an annual basis. Of course, companies have always had some awareness of the fact that turnover costs money. But it is not until recent years that researchers and consultancies alike have started to gauge the actual magnitude of these costs. Let’s take a closer look at the cost of churn.

To begin, the costs should be including all the expenses related to replacing the old employee - that is, finding, hiring, and getting the new person to the level of productivity of the last one. These costs include advertisements, the fee or salary paid to the recruiter, time spent on interviewing, reference checking, testing, and training, and suboptimal productivity during the onboarding period.

However, the expenses also include opportunity costs. The organization may lose out on business opportunities during a period of vacancy. This can either be because the employee who left was a skilled business person him- or herself, or because the recruitment of a new person takes so much time and effort that other tasks suffer meanwhile.

There is also the cost of diminished ROI. For instance, US firms spend about 15 billion dollars a year on employee training and 800 billion on incentives. Attrition decreases the return on those investments.

One often-mentioned number is that churn costs at least 0.5 of the employee’s annual salary. However, this figure quickly increases for highly skilled workers. All in all, Josh Bersin at Bersin by Deloitte estimates that a well-performing employee leaving can cost the organization between 1.5 and 2 times that person’s annual salary. Similar numbers are given in a report for Center for American Progress by Boushey and Glynn (2012).

As you quickly realize, churn costs are difficult to generalize as they differ significantly between different positions, individuals, departments, companies and industries. However, one general conclusion tends to apply regardlessly: Churn is significantly more costly than most executives think. Finding ways of predicting and preventing it is thus pivotal.

Why people quit their jobs

Quite a lot of research has been devoted to the question of what drives churn. If you condense the research results to a really brief summary, however, one could say that people leave their jobs for three broad reasons: they don’t see enough development opportunities, they don’t like their boss, or they are offered a better job.

Another question is: Who leaves? One study included 6727 salespeople in 1058 stores. Researchers expected high performers to be less likely to leave, and this also turned out to be the case. The highest performers were more prone to staying, which could be because they are more recognized by the organization. However, the study showed that also the low performers were unlikely to leave. It was the middle-performing salespeople that were most prone to quitting. This is quite serious news, if you consider that this group make up the bulk of the organization.

Interestingly, peer effects were the strongest predictor of quitting. That is; people’s propensity to leave was highly influenced by how their colleagues were behaving. For instance, when there was little variation in performance in the workgroup, people were more likely to quit. One explanation, according to the authors, is that companies without much variation in performance do not make people feel challenged, hence providing less motivation at work. Also, turnover tended to be contagious: Once people started quitting, others tended to follow.

Certain non-work factors have also proven to have a huge impact on job-hunting, such as milestone birthdays or class reunions. Jumping to 12 % before birthdays and 16 % after reunions, from an average of 6 %, turnover seems to be sparked by events that mark the passage of time. Likely, these events make people think more about what they want to get out of life and whether they need to make a change to get it.

Predicting Turnover

As we have seen, turnover is a costly phenomenon that can significantly harm organizations’ performance. So what do organizations need to do in order to reduce it? One thing is for sure: It is not enough to react when churn is already a fact. In order to curb turnover, organizations need to be proactive. Because even though churn is a complex phenomenon, that does not mean that it happens by chance. Rather, organizations should make use of data and analytics to predict who is likely to quit and when. Big data allows companies to identify variables that predict turnover. These variables can help managers assess whether an employee is low, moderate or high risk of quitting.

Research has shown that employees about to quit tend to display a number of specific behaviors. One study from Utah State University and Arizona State University identified 13 behaviors of people likely to quit. These included:

  • Decreased work productivity
  • Acting less like a team player
  • Doing minimum amount of work
  • Less interest in pleasing managers
  • Less willingness to make long-term commitments
  • Negative change in attitude
  • Less focus on job-related matters
  • More frequent expressions of dissatisfaction with work and supervisor
  • Leaving early more frequently
  • Less interest in working with customers.

By detecting behaviors such as these, organizations can anticipate risk of churn and address it in time, before it costs you your strong performers.

Importantly, however, the above behaviors only represent a generalized picture based on a large number of organizations. The real magic happens when you start to explore what drives turnover in your specific setting. Analyzing what characterizes your leavers helps you spot the things that are causing attrition, and also points out the specific warning signs to look for. As an example, Credit Suisse identified employees at the risk of leaving and had internal recruiters call them up to tell them about open internal positions. The company reduced its attrition by 1 %, saving between 75 and 100 million dollars in rehiring and training costs.

However, the prediction of turnover also calls for moral considerations. Certain actions taken to detect risk of churn are highly questionable from an ethical perspective, such as analyzing email and social media activity for clues or even an employee’s use of ID for entering or exiting the building at odd hours.

.

Retaining your employees

As we have seen, data and analytics can be a great way of circumventing churn. Nevertheless, predicting turnover is of course just a first step - next, you need to figure out what to do to keep your high-performing employees. Again, one of the best things to do is to look to research for guidance. Today, training and incentive programs are often applied without the science to back it up.

Overall, researchers agree that interventions are better to deal with employees that might leave than waiting for an offer to counter it: 50% who accept a counteroffer are gone within 12 months anyway. Further, increasing compensation alone does not do it for an unhappy employee. Instead, you should focus on opportunities for growth: Find out more about the person’s long-term goals, what skills they want and need, and emphasize their possibilities to make an impact. Ambitious high-performers want to feel like they are part of something that matters. In the long run, this also entails fostering a caring and appreciative environment that values their work.

Based on research, managers should also pay extra attention to peer effects, i.e., situations where people quit because of how their colleagues are behaving. For instance, people might quit because other people quit. Therefore, if no sooner, managers should at least launch interventions when there have been a couple of instances of voluntary turnover in a group. At this point, the risk of contagion is high. Having conversations with remaining employees about their goals and desires for development is thus well-invested time.

But let us not forget the other important aspect of retention: Understanding why employees stay. Besides exit interviews, you should consider performing stay interviews. What compels high-performers to remain? This is also a great opportunity to praise and reward them.


AUTHOR

Linnea Bywall

Psychologist at Alva Labs

Linnea is a licensed psychologist working organizational psychology at Alva Labs, focusing in assessments and leadership development.

linnea@alvalabs.ioLinkedIn

Contact

Contact us: mail@alvalabs.io